With the rapid progress in recent years, techniques that generate and manipulate
multimedia content can now provide a very advanced level of realism. The boundary …

Easy access to audio-visual content on social media, combined with the availability of
modern tools such as Tensorflow or Keras, and open-source trained models, along with …

AI-synthesized face-swap** videos, commonly known as DeepFakes, is an emerging
problem threatening the trustworthiness of online information. The need to develop and …

The modern computer graphics pipeline can synthesize images at remarkable visual quality;
however, it requires well-defined, high-quality 3D content as input. In this work, we explore …

We present dynamic neural radiance fields for modeling the appearance and dynamics of a
human face. Digitally modeling and reconstructing a talking human is a key building-block …

This paper presents a method to automatically and efficiently detect face tampering in
videos, and particularly focuses on two recent techniques used to generate hyper-realistic …

Conditional image-to-video (cI2V) generation aims to synthesize a new plausible video
starting from an image (eg, a person's face) and a condition (eg, an action class label like …

In this paper we propose a novel image representation called face X-ray for detecting
forgery in face images. The face X-ray of an input face image is a greyscale image that …

The free access to large-scale public databases, together with the fast progress of deep
learning techniques, in particular Generative Adversarial Networks, have led to the …

In recent months a machine learning based free software tool has made it easy to create
believable face swaps in videos that leaves few traces of manipulation, in what are known …